The latest Gartner Magic Quadrant for Data Science and Machine Learning Platforms has just been released, and IBM is delighted to be recognized as a Leader in the space. Watson Studio on IBM Cloud Pak for Data, a modular, open and extensible platform for data and AI that combines a broad set of descriptive, diagnostic, predictive and prescriptive capabilities. Organizations seeking to more efficiently run and manage AI models, simplify their AI lifecycle management, and empower their data scientists with technology that can help optimize their data-driven decision-making can turn to IBM Watson® Studio. The product builds upon trusted solutions, because of that IBM now delivers a modern and comprehensive solution that leverages its roots in SPSS, ILOG CPLEX and other earlier products, complemented by a stream of innovations from IBM research, comprising a well-rounded vision.
Further, IBM Watson Studio helps organizations to build and scale AI across their organization with trust and transparency by automating AI lifecycle management. Deploying AI with continuous model governance enables users to accelerate time to discovery, prediction, and outcomes while keeping AI explainable and tuned to any organization’s business demand. It empowers customers to organize data, build, run and manage AI models, and optimize decisions across any cloud using IBM Cloud Pak® for Data. To ensure that an organization’s AI automated technology is helping make sound decisions, IBM offers extensive support for explainability, bias, fairness, accuracy and drift monitoring, synthetic data and differential privacy. Because of this, you can use your data with confidence and peace of mind.
Finally, the entire IBM Cloud Pak for Data platform is designed to provide customers with the flexibility to deploy IBM’s offerings such as IBM Watson Studio, IBM Knowledge Catalog, IBM Db2, and IBM DataStage on the vendors of their choice. Building on the hybrid-cloud foundation of Red Hat® OpenShift®, IBM Watson Studio on IBM Cloud Pak for Data simplifies the process of deploying almost any open-source project to production with containerized resource and infrastructure management efficiency.
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.